You’ve learned countless different means that you have the right to represent data and also modify your maps. Geographer mark Monmonier argues that all of these tiny modifications—smoothing of geographical features, choices about classification scheme, aggregation that data, or clever usage of hue—represent tiny “lies.” he writes, “To portray coherent relationships for a complex, three-dimensional civilization on a level sheet of file or a video clip screen, a map must distort reality…There’s no escape from the cartographic paradox: to existing a useful and also truthful picture, precise map have to tell white lies.” (1996)

White lies include all sorts of cartographic strategies, consisting of symbolization, generalization, and also unintentionally misleading mistakes. Then there room the other kinds that lies—propaganda maps, heralding maps, maps for armed forces defense and disinformation, and also maps that press a details political perspective. As a an important map reader and map maker, that is imperative that you be able to identify and understand all of the ways that maps lie. In this chapter, we are going to emphasis on how and why maps lie, even if it is innocently or not so innocently.

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By the finish of this chapter, you should be able to critically read the maps the you conference in your day-to-day life—whether basic informational maps or maps through a more complex social or political message—and understand the techniques that the mapmakers have actually chosen to promote a specific message or highlight specific data features. In stimulate to be a an important map reader, pay attention to the guiding inquiries in package on the right.

The assorted mapping strategies that you’ve learned around in this food all job-related together to create a specific an outcome in the last map. The mapping selections that are made have the right to have a large impact ~ above the last product. Together we will view a tiny later in this chapter, these choices—and the lies the they tell—can likewise have real-world consequences for people and societies.

This thing will present you come guiding concerns in thinking about lying maps:

Who do this map and why?What is included and also what is excluded indigenous the map?What is the source of the data top top this map?Which alteration strategies room at work in this map? What is the effect?7.1 small lies

7.1.1 Projection

All maps inherently encompass white lies and also subtle misrepresentations: this white lies are fundamental to the an extremely act of mapping! Think back to our discussion of projection. Recall that only a 3-dimensional object is able to preserve both shape and also area, therefore anytime you translate a 3-dimensional thing onto a 2-dimensional surface, you must choose how you space going come distort the object.

This misrepresentation is a kind of lying with projection. One instance that has actually garnered much attention is the difference in between the Mercator and also Gall-Peters projections. The Mercator estimate was produced by Flemish cartographer Gerardus Mercator in 1569 and is used in plenty of settings, native classrooms to Google Maps and also other digital services. This map to be primarily produced navigation and also it conservation angles and shapes well. The major drawback come this projection is that it go not keep area, for this reason that nations near the poles show up much bigger than they must relative to nations near the equator. Greenland has only 7-percent of the land area the Africa, for example, but it shows up to be just as huge on the map.

In contrast, the Gall-Peters projection preserves area in ~ the cost of shape (e.g., Greenland is considerably distorted however the size of that area is exactly in comparison to Africa). Dr. Arno Peters in the 1970s said that the Mercator projection could introduce prejudice into the late of the world, offered that nations in the northern latitudes were perceived as much bigger than those closer to the equator. As a result, Peters argued, the Mercator projection shows a northern-centric bias and alters the world perception of the prominence of the an international south. He offered an alternative, the Peters projection, that far better preserved area. It transforms out that this project existed lengthy before, having actually actually been designed by James bitterly in the 1800s, however the estimate is usually termed the Gall-Peters projection to identify Peters’ argument.


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Lying with projections. The Mercator and also Gall-Peters projections are both exactly in the feeling of being an excellent projections but present the world differently. <1>

7.1.2 Symbolization

Because that is difficult to display or even to acquire all of the details that can be mapped in a certain area, symbolization is a common way in i beg your pardon mapmakers “lie” in bespeak to current or highlight specific information.

Compare the Google Maps road map of Boston in the figure listed below to the satellite image equivalent. The image and also map stand for the same area, but in the road map, Google supplies symbolization come tell white lies—highlighting different roadways utilizing size and hue (federal highways in thick orange, state highways in yellow, county roadways in thick white, city roads in slim white), different shapes to denote different species of highways, and different label layouts for various towns and neighborhoods in the area. These develops of lying v symbolization assist to accomplish one that the main purposes that Google Maps: clear presentation of information. You would be hard-pressed to use the life imagery to do beneficial things prefer drive approximately Boston or discover locations favor Cambridge. Top top the various other hand, the image can be an ext useful to do guesses about urban floor cover in the Boston region or just how deep the water is in the harbor.


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Lying with symbolization. Google Maps see of Boston and also satellite view of Boston are of the very same area however use symbolization differently. <2>


Cartograms are another method of lying v symbolization. Cartograms space maps that distort area or street by substituting an additional thematic variable. Due to the fact that of the dramatic distortions the cartograms produce, friend might think about them to be telling much more than white lies. However, cartograms space just various ways of symbolizing the exact same data in order come tell a story. The large lies that we talk about in the following section are lies that are told because that very certain purposes or for eliciting details reactions. Cartograms are thought about white lies here since they are just another set of symbolization options that affect the depiction of data on your map.

The figure listed below is an example of a map mirroring the number of people and also the lot of riches per country in 2015. Note how the size of any given nation is not displayed in accordance through the land massive of that country, yet in fact, synchronizes to the variety of people living there or its complete wealth. This map gives you, an extremely quickly and effectively, a read on which nations have the many people and most money.


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Lying v cartograms. Population total and also wealth by country in 2015. Note how the dimension of countries on the map is no their yes, really area however instead proportional to the attribute gift measured, populace or wealth. <3>

7.1.3 Standardization

How and whether data is standardized likewise has a large impact top top the story that the map tells. The maps in the figure listed below represent poverty data native the 2000 us census. The top map standardizes data by the percentage of the populace – the variety of people life in poverty family member to the total population of that census tract. The bottom map is based upon raw number for how many people are life in poverty in the census tract. By failing come account for poverty together a percentage of the full population, the bottom map tells a lot bigger lie about poverty level in the US.


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Lying through standardization. Poverty together a percent versus poverty together a life number. This maps stand for poverty data from the 2000 us Census but differ in your standardization. <4>

7.1.4 Classification

Classification matters. Selections you make about how come classify her data can have a big impact top top the story the your map tells. The maps here show how you deserve to lie with classification. The 3 maps in the figure below each use the exact same data, the same variety of classes, the same color scheme, and the very same standardization, yet each tells a really different story around poverty in the US, depending on the category scheme. The an initial map classifies the data utilizing equal interval, the 2nd using natural breaks, and also the third using a quantile scheme.


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Lying through classification. Poverty via equal interval, natural breaks, and also quantile classifications. The 3 maps usage thesame data, the same number of classes, the same shade scheme, and also standardization, yet each tells a really different story around poverty in the US. <5>

The figure below shows three maps of 2000 census poor data. Each uses a quantile group scheme. The only distinction is the number of classes. See how the variety of classes results your late of poverty level in the US. Although there are some locations that show patterns that poverty throughout the three maps, as you rise the variety of classes, you gain a an ext nuanced picture of just how poverty is distributed across the country.


Lying v classes. Poor via quantile classifications with a differing number of classes. The three maps use the very same data and also color scheme yet tell a different story about poverty in the US. <6>

7.1.5 Aggregation, Classification, and also the environmental fallacy

Recall that data are regularly aggregated. They room often gathered at one scale, such as the family or neighborhood, and then report at much broader scales, such as the census tract or county. This is termed aggregating the data. While aggregation have the right to be very helpful in state of keeping privacy or presenting a broader and synoptic view, that can likewise lead to the ecological fallacy, or the presumption that a properties or worth calculated because that a team in aggregate can be applied to an separation, personal, instance member of that group. In other words, aggregated data do it tough to assume or guess at the qualities of any type of given individual uncovered in the aggregated area.

Imagine you are comparing the earnings of 2 blocks, every being composed of five households. Block A has an average family income that $48,000 if Block B has actually an average family members income the $40,000, per the number below. In which area space you much more likely to find a household with a higher income? If you decided Block A—the area v the higher average income total—then you were tricked through the ecological fallacy. In fact, there is no method to recognize from aggregated data alone what the situation is choose for an individual in ~ a group. The figure shows one of many possible scenarios under which 4 out of five family members in Block B have higher incomes than families in Block A.


Ecological fallacy. Take into consideration this scenario in i m sorry Block A has actually a greater aggregated typical income however mostly lower individual values than Block B. <7>

Watch out for the eco-friendly fallacy anytime you room interpreting maps, or you might come to false conclusions about the world who live in a community or other areas!

The danger of the eco-friendly fallacy because that the map leader is carefully tied come the subtle means that mapmakers can lie v aggregation, regularly in mix with classification. The figure listed below illustrates poll returns for the 2012 united state presidential election. The map on the left represents counties through their bulk vote in the election. Red signifies counties where a bulk of inhabitants voted for the Republican candidate, Mitt Romney; blue signifies counties v a majority vote for the autonomous candidate Barack Obama. The map top top the right attempts to expose a little an ext nuance in vote patterns, by making use of a red-purple—blue range to show percentages of votes, when the one ~ above the left is less complicated and more prone come the environmental fallacy. This maps space both totally correct. They different in exactly how they classify their underlying data right into either two categories or by no classifying the data and also instead of utilizing hue and also value to stand for fine differences amongst counties.


Lying through aggregation and also classification. Lying, or quite telling different truths, about the United says presidential choice in 2012. The map on the left reflects counties by their majority vote in the election, wherein red means counties wherein a bulk of inhabitants voted because that the Republican candidate and blue signifies counties vote Democrat. <8>

From your knowledge of the eco-friendly fallacy, you know that also at the level the the county, this map does not accurately represent the party affiliation, beliefs, or voting patterns of each human in the county. The data space aggregated come the ar level and also are classified in different way than the data in the map on the right. This kind of aggregation and classification is useful because it enables us to distinguish in between voting trends in different parts the the country—rural/urban variations, because that instance. The map top top the best is tho lying the course—not all inhabitants in the united state voted, and those that did were not necessarily voting because that the endorsed Republican or autonomous candidate—but the is do the efforts to provide a more accurate picture of the data. Both maps lied in bespeak to offer a snapshot of the election outcome in specific parts that the country.

Consider the cartogram version of the choice map, below. The cartogram distorts area based on county-level choice returns, therefore counties with larger populations show up bigger. The cartogram lies by distorting area, yet in some ways, it gives us a clearer snapshot of election results. In the typical county aggregation map over it appears that the united state voted strong Republican; however the cartogram reflects that numerous Republican-leaning counties have relatively small populations, if counties with bigger populations mostly voted for the democratic candidate.


Election cartogram. This cartogram of election outcomes distorts apparent county area by the number of returns, for this reason counties with bigger populations show up bigger.<9>

7.1.6 Aggregation and Zonation

We have looked at just how data space aggregated to larger areas and also how this process of aggregation can affect how data are interpreted, such as resulting in the potential for the environmental fallacy. In enhancement to aggregating data, us can also zone the differently, which is another way of saying us can attract an virtually infinite array of differing borders for any kind of given aggregation. We often use county boundaries in ours analyses, because that example, however the borders of counties are arbitrary. They were attracted over time follow to a variety of various principles, such as where a flow flowed or where negotiation was being encouraged. Population data is frequently aggregated and reported by county yet they might be (and regularly are) report via various other zonations, such together zip codes, phone-number area codes, school districts, or watershed boundaries.

Importantly, the means in which data room aggregated and also where the limits of area are drawn can easily adjust data trends and evaluation outcomes. Relying on the range at which girlfriend look at a geographic pattern, you can derive totally different outcomes from the specific same basic data. This is referred to as the modifiable areal unit problem. Because that example, consider the price of a condition in a population. Individuals at specific locations become sick, however health officials regularly want to recognize the more comprehensive trends the diseases. Therefore – and to defend the privacy of patient – they may count the number of cases by block, zip code, or an additional zonation. However artificially breaking up space into these larger areas can readjust the noticeable patterns of disease. The figure listed below illustrates this for deaths from respiratory problems in Ottawa, Canada. Every map supplies the same underlying data yet groups or zones instances differently: by a health and wellness department aggregation, through neighborhood, and by census tract. Each classes spatial units into quartiles, or in various other words, divides the areas into four equal teams by how many civilization are dying in those areas. Note that these three maps all usage the same specific underlying data and also are simply using various ways the zoning the groups. Nonetheless, this maps look very different, highlighting the an obstacle of the modifiable areal unit problem.


Health and also zonation. This maps all display data on where world die native respiratory troubles in Ottawa, Canada. Every map provides the very same underlying data but groups or zones situations differently. Every categorizes spatial units into quartiles. <10>

In enhancement to zoning, the modifiable areal unit problem can an outcome from aggregation. Consider the figures below of solar potential in the lower 48 joined States. Solar potential describes the suitability that a certain place to develop solar power. This data room from the nationwide Renewable energy Laboratory and these maps were developed by Anthony Robinson (2010). The first map shows the average annual solar potential through state. In various other words, this data room aggregated through state. You have the right to see ideal away that some states look better than others.


Solar potential by state. Yearly solar potential through state, which procedures the suitability that a certain place to develop solar power. <11>

The exact same underlying data aggregated to counties rather makes the look like a the majority of states the were presented in one color at the state level actually encompass several category of solar potential as soon as you look at the data through county.


Solar potential through county. Annual solar potential by county, which steps the suitability of a specific place to construct solar power. <12>

The 3rd map reflects the initial underlying data on which the other two maps were based. These original data calculation solar potential in 10-kilometer grid cells. You have the right to see just how the state and also county limits compare come the life data and also how aggregation alters the evident distribution of phenomena.


Solar potential by net cell. Annual solar potential given by the original data, which offered a 10km net cell. <13>

7.2 huge Lies

There are various other mapping lies that space not therefore innocent. In the remainder the this section, we are going to focus on some examples of maps that space lying more debetterworld2016.orgerately—or working difficult to stand for a very specific story. Store in mind, though, the there is a fine line between the map-maker intending clarity vs. Advertise an agenda. The first example addresses the means that aggregation and zonation are manipulated to accomplish a particular political end.

7.2.1 political Lies: Gerrymandering

There are plenty of ways that maps space modified in order come promote details political perspectives or outcomes. Political lies in mapping take it the form of propaganda, project advertisements, and politically-motivated source maps. One particularly important politics lie is gerrymandering, the manipulation the the borders of an electoral constituency in order to donate a certain political party or group. Due to the fact that US congressional districts are reapportioned in the years adhering to the decennial census, political leader in power at that time might take the chance to redraw borders—even convoluted gerrymandered borders—that favor their party’s continued political success.

Gerrymandering has been vital and highly contested component of the us political procedure for quite some time. The term to be coined in the Boston Gazette in reference to the contrived redistricting schemes designed to secure the political power of Massachusetts governor Elbridge Gerry’s Democratic-Republican Party. In 1812, the Gazette published the illustration seen listed below comparing Gerry’s convoluted redistricting to the photo of a salamander-like creature. Thus, “gerrymandering” to be born. This political method has a storied history, and is a powerful method of lying v maps: gerrymandering functions to consolidate or distribute political power, v such methods as isolating opponents (known together packing) and breaking up locations of the contrary (cracking).


Gerrymandering. The hatchet gerrymandering was coined through Elkanah Tisdale in the Boston Gazette in 1812. The newspaper published an editorial cartoon that confirmed the elongated shape of the aggregated areas in the kind of a salamander. <14>

In the number below, there space fifty precincts (the smallest area in i beg your pardon votes are tallied) that can be distributed amongst five districts. At the precinct level, there room proportionally more green voters 보다 yellow (60% versus 40%), and so all various other things gift equal, friend would expect non-gerrymandered districts to reproduce a proportionate outcome. The end of the five complete districts, friend would suppose three to vote bulk green and also two majority yellow, which synchronizes to the 60% versus 40% separation of the basic precincts. Grouping precincts into districts yield different outcomes if principles of gerrymandering room used, namely packing and also cracking. Under Districting A, the variety of districts won by each party is proportional to the number of voters because that each party: 60% for green and also 40% for yellow. Districting B crack the yellow precincts in a method that allows green to conquer all districts, yielding 100% because that green and also 0% because that yellow. Districting C packs and cracks environment-friendly in a way that lets yellow eke the end an upset win with three districts, which is the reverse of the underlying voting patterns of the precincts.


Packing and also cracking. Overall, at the precinct level, there room proportionally an ext green voters than yellow (60% vs. 40%). Three different ways of grouping precincts right into districts yield different outcomes. Under Districting A, the number of districts won by each party is proportional to the variety of voters because that each party. Districting B crack the yellow precincts in a means that allows green to overcome all districts. Districting C packs and cracks environment-friendly in a method that allows yellow obtain an upset win with three districts. <15>

Gerrymandering is alive and also well today. It is widely practiced in the US, together you deserve to see by several of the much more outrageous instances of congressional gerrymandering in the figure below. This kind of redistricting and reapportionment can have really real results for civilization who live in this areas, limiting their representation, protecting incumbent seats, and compromising access to federal funding. Part have suggested that gerrymandering is akin come legal election rigging.


Gerrymandering in the joined States. These maps display examples of gerrymandered districts in the joined States; this are just a couple of of many. North Carolina’s 12th congressional ar in 2016 was an example of packing, with mostly African-American inhabitants (top). Illinois’s fourth congressional district packs two Hispanic locations while meeting the requirement for contiguity running along Interstate 294 (middle). Ohio’s 7th is an instance of “cracking” whereby the urban populace of Columbus, Ohio is split off into an ext conservative suburbs. <16>

For incarcerated populations and those that live in districts wherein prisons room located, gerrymandering may have an even bigger impact. In order come understand just how prison-based gerrymandering works, you’ll need to think earlier to what you learned around how census data is collected, analyzed, and aggregated. For particular data categories, the Census bureau counts incarcerated people as residents of the town wherein their prison is located, quite than the town wherein they resided prior to their imprisonment. Due to the fact that census data are right now used for redistricting at every levels the federal, state, and local governance, the certain cities and census tracts where civilization are counted is very important for ensuring representation and apportionments.

In the US, the prison population has risen significantly in the past few decades. Advocates for ending prison-based gerrymandering argue the counting prisoners based upon their incarceration location—particularly once those detainees are barred from voting in 48 states—gives exponential political power to the little non-incarcerated populace in the area, and their representatives. When this happens, advocates argue, the exercise siphons political representation and funding from other districts in the state—particularly those districts that bear the greatest costs of crime.

The jail gerrymandering dynamic is obvious in currently census maps. Let’s return to the Los Angeles area income and education maps that you encountered in chapter 6. The figure below contains details around Los Angeles county Census tract 2060.20. The map reflects us the income and education space not correlated in this area. Looking at the data, we check out that only 5.328% the the population in this tract has actually a Bachelor’s degree, however 91.453% has actually an yearly income that $75,000+. Only when we dig a small deeper go this specific tract begin to make a little more sense. Census tract 2060.20 is house to the pair Towers Correctional Facility and also the Men’s main Jail. The ACS and census at this time tabulate every one of the detainees who live in the pair Towers and also Men’s main jail together residents and also takes into account their education level. However, the census walk not incorporate incarcerated populaces in family income or poor calculations, therefore the map top top the right only takes right into account the incomes of the neighboring community. You have the right to see exactly how this type of data collection an approach might make it very complicated to adequately account for population, ensure reasonable representation, and manage appropriations in prison-based communities, and the areas from i m sorry incarcerated populaces come.


Prison gerrymandering. This detail of Census tract 2060.20 mirrors income and also education (Left: Income an ext than $75,000; Right: education Bachelor’s level or More). This maps display us that income and also education are not correlated in this area. <17>

7.2.2 political geography Lies: challenged Territories

There room other types of lies that have more to carry out with navigating the complexities of international geopolitics. Because that instance, in countless parts of the world, there room territories that space contested in between two or an ext states. Depending upon the political considerations of the mapmaker and the audience, local maps might represent this territories really differently. Jammu & Kashmir is a territory in the northwestern an ar of south Asia follow me the boundaries of India, Pakistan, and China. Due to the fact that the 1947 partition of british India produced the modern-day states the India and Pakistan, the two countries have been involved in a territorial conflict over the region. Jammu and Kashmir are geopolitically far-ranging and space the resource of the Indus River and its tributaries, i m sorry sustain India and Pakistan’s water supplies.


Situating Kashmir. Jammu & Kashmir is a territory in the northwestern an ar of southern Asia along the borders of India, Pakistan, and China. <18>

India and Pakistan both insurance claim Jammu and Kashmir. The figure listed below shows how Google Maps pictures of the an ar appear in different way whether the search is conducted in the united state (which considers the two states’ territorial insurance claims on Jammu and Kashmir to be unsettled) or India (which reasserts its claim to Jammu and Kashmir in the map).


Contested Kashmir. Google Maps will display the challenged Kashmir an ar differently depending upon whether the user is in the United says or India.<19>

Different media establishments have likewise favored different representations of Jammu and Kashmir, as checked out below.


Kashmir in the news. Competing media depictions of Kashmir. Various media organizations favor various representations of Jammu and Kashmir. <20>

7.2.3 advertising Lies: Advertising

In 2009, at & t filed a lawsuit in commonwealth court versus Verizon. The complaint? at&t alleged that a Verizon ad campaign special coverage maps of every carriers’ 3G moving data company misrepresented the actual reach of AT&T’s wireless service and also misled customers. AT&T sued Verizon end a “lying map.” at&t was concerned that the map would certainly make customers think that its entire wireless network to be reflected in the spotty map below, when Verizon completed that the map accurately reflected the differences in between the two carriers’ 3G networks. At&t dropped the suit about a month after ~ it to be filed, but it raises some necessary questions around lying maps in advertising.


Lying competition. At&t alleged that a Verizon advertisement campaign “There’s a Map because that That” featured coverage maps of each carrier’s to move data business that misrepresented the actual with of AT&T’s wireless service and also misled customers. <21>

For mobile organization providers, maps that demonstrate extensive coverage are ending up being increasingly vital as companies choose Verizon and also AT&T compete for larger shares that the marketplace. However, plenty of consumers have actually expressed frustration over what castle perceive together inaccurate coverage maps in the advertising materials of mobile phone service providers. In recent years, a variety of apps and websites have actually popped up to crowd-source mobile phone coverage data throughout the US and paint a much more accurate picture of mobile network coverage. The figure listed below shows a crowd-sourced map from one such site, betterworld2016.orgSignal.com.

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betterworld2016.org mapping. This crowd-sourced cell phone network coverage map indigenous betterworld2016.orgSignal.com is arguably much less biased 보다 those readily available by companies since firms have actually a vested interest in making their product seem better than competing offerings. <22>

7.3 Conclusion

In making maps, we tell many lies. Small lies incorporate all species of standard cartographic strategies, including projection, symbolization, standardization, classification, aggregation, and also zonation. Climate there space the other kinds the lies—gerrymandering, propaganda maps, maps that press a particular political perspective, and misleading advertising maps. As a an important map reader and also map maker, the is imperative that you be able to identify and understand the means that maps lie.

Resources

For an ext information around lying with maps:

Mark Monmonier. 1996. Just how to Lie v Maps (University that Chicago Press)

For more perspectives on gerrymandering: